论文标题
用解释性证据回答计数查询
Answering Count Queries with Explanatory Evidence
论文作者
论文摘要
网络搜索和问题回答的一个挑战性案例是计数查询，例如\ textit {“约翰·列侬的歌曲数”}。先前的方法只是用单个，有时令人困惑的数字回答这些方法，或返回具有不同数字的文本片段的排名列表。本文提出了一种用推理，上下文化和解释性证据来回答计数查询的方法。与以前的系统不同，我们的方法不从多个观察结果中取出最终答案，支持计数的语义限定符，并通过列举代表性实例提供证据。各种查询的实验显示了我们方法的好处。为了促进对这个未经激动的主题的进一步研究，我们发布了一个带有200K相关文本跨度的5K查询的注释数据集。
A challenging case in web search and question answering are count queries, such as \textit{"number of songs by John Lennon"}. Prior methods merely answer these with a single, and sometimes puzzling number or return a ranked list of text snippets with different numbers. This paper proposes a methodology for answering count queries with inference, contextualization and explanatory evidence. Unlike previous systems, our method infers final answers from multiple observations, supports semantic qualifiers for the counts, and provides evidence by enumerating representative instances. Experiments with a wide variety of queries show the benefits of our method. To promote further research on this underexplored topic, we release an annotated dataset of 5k queries with 200k relevant text spans.
